Narrow Results

Taking the unique advantage of the cryptocurrency market setting, this paper examines the relationships between blockchain participation and returns, trading volume and realized volatility of main cryptocurrencies (i.e., Bitcoin, Ethereum and Litecoin). Dissimilar to previous theoretical studies that model the influencing factors on participation, we employ the number of unique from addresses¹ as the proxy for cryptocurrency investors’ blockchain participation and further explore the impact of such participation. By using vector autoregressive (VAR) model, we find that the blockchain participation has a significant and positive impact on the next day’s trading volume and realized volatility for the main cryptocurrencies. Our results are robust to the Granger causality test and alternative measure for blockchain participation.

Vector error-correction models (VECM) are increasingly being used to capture dynamic relationships between financial variables. Estimation and interpretation of such models can be enhanced if zero restrictions are allowed in the coefficient matrices. Conventional use of full-order models may weaken the power of statistical inferences due to over-parameterization. The paper demonstrates the usefulness of this approach for the analysis of exchange rate relationships. Specifically, the paper examines the relationship between the money supply and the Euro and provides a test of purchasing power parity (PPP) in Japan. The latter test results shed light on the adjustment mechanisms through which PPP is achieved. In addition, it is clear that the proposed ZNZ patterned VECM modeling provides better insights from this kind of financial time-series analysis. The paper also shows that causality detection in an I(d) system can be revealed identically from the ZNZ patterned VECMs or the equivalent VAR models.

This study empirically investigates the interaction between trading volume and cross-autocorrelations of stock returns in the Taiwan stock market. The result shows that returns on high trading volume portfolios lead returns on low trading volume portfolios when controlled for firm size, indicating that trading volume determines lead-lag cross-autocorrelations of stock returns. Overall, the empirical findings of this study demonstrate similar results for both monthly and daily returns, suggesting that nonsynchronrous trading is not the main reason for the lead-lag cross-autocorrelations presented in this study. Consequently, the empirical results presented here support the speed of adjustment hypothesis, and suggest that some market inefficiency exists in the Taiwan stock market. Additionally, compared with evidence of lead-lag cross-autocorrelations in the larger, less regulated US stock market, as examined by Chordia and Swaminathan (2000), Taiwan stock market displays less evidence of VARs and Dimson beta regressions. We conjecture that this weak evidence may result from the regulations limiting daily price movements in the Taiwan stock market. Although the price limits policy lowers risk and stabilizes stock prices, it also prevents stock prices and trading volume from instantaneously and fully reflecting new information.

This paper examines the dynamics of returns and order imbalances across the KOSPI 200 cash, futures and option markets. The information effect is more dominant than the liquidity effect in these markets. In addition, returns have more predictability power for the future movements of prices than order imbalances. Information seems to be transmitted more strongly from derivative markets to their underlying asset markets than from the underlying asset markets to their derivative markets. Finally, domestic institutional investors prefer futures, domestic individual investors prefer options, and foreign investors prefer stocks relative to other investor groups when they have new information.

This paper examines the informational role of trades in the corporate bond market. Using transaction data, we compare the temporal relation between volume and volatility of returns for both bonds and stocks issued by the same firms. We find a dramatic difference between these two securities. While there is a strong positive relation between return volatility and volume for stocks, this relation is much weaker for corporate bonds. This finding holds not only for straight bonds but also for callable and convertible bonds. Empirical evidence reveals a very different relation between volatility and volume in the corporate bond market than predicted by standard microstructure models. Results show that the role of volume and trade frequency can be quite different across asset classes.

This paper explores the cointegration between agricultural commodity prices, crude oil prices and exchange rates. Vector autoregressions (VAR) or vector error correction models (VECMs) are applied to price data for French maize and milling wheat, U.S. corn prices and spot and future oil prices. The series are split between 2000-2007 and 2009–2019 omitting the “Great Recession” allowing for analysis of structural market changes. While oil prices influence futures pricing, the link is neither stable nor widespread. Modeling of time series in search of cointegration must consider structural market changes. Results from a “one-model-fits-all” approach are unlikely to be satisfactory.

Engineers and designers from automotive and aerospace sectors have been using 3D printing (3DP) for decades to build prototypes. However, 3DP became popular only recently. This paper is divided into three sections. Section 1 is introductory in nature, which deals with current trends, the modeling process of printing and deliberation on different categories of 3DP. Section 2 deals with the research methodology. An exquisite technique to study innovation dealing with time series data, called the vector autoregression (VAR), is performed to analyze the world patent data on 3DP, based on the information provided by the Government of UK and the International Monetary Fund (IMF). Section 3 attempts to forecast future trends on 3DP by using two techniques viz. impulse response function and variance decomposition. The VAR analysis performed revealed that GDP is not directly instrumental in the advancement in patenting of 3DP technology. Results captured by way of impulse response function suggest that when a shock is given to PR itself, it decreases sharply, whereas when a shock is given to investment, PR undergoes a steady decline. Thus, if there is any adverse shock imparted on investments, it directly reduces the patent ratio. Lastly, when an impulse is given to GDP, PR continuously increases, which implies that increase in GDP causes hike in investment which ultimately increases PR. The results of variance decomposition indicate that in the initial periods, PR itself explains the maximum variance, followed by the GDP and to the least by investment. The changes observed with the trend of explanatory character of variance imply that more investments in technology are instrumental in increasing patent ratio in the G7 countries as per the vector error correction (VEC) model developed here. Though during the nascent stage of emerging technologies investment in technology may not necessarily increase the patent ratio, the result obtained brings to light interesting insights.

The main objective of this paper is to test for the possibility of an optimal currency area (OCA) in the six Gulf countries (namely: Saudi Arabia, Bahrain, Qatar, Kuwait, Oman, and United Arab Emirates (UAE)). To constitute such an OCA, however, they must satisfy certain preconditions; i.e., they must have similar economic structures with exposure to symmetric shocks, they must be open, well-diversified economies, and they must also ensure a high degree of factor mobility. The objective of this paper is to assess the degree to which the Gulf Cooperation Council (GCC) meet the requirements of an OCA. Annual and quarterly data are used in our analysis. Using a multivariate threshold autoregression (MVTAR) model and generalized response functions, the main results are that the GCC countries should be divided, as far as the symmetry of the shocks is concerned, into two sub-groups. The first consists of UAE, Oman, and Bahrain and the second consists of Saudi Arabia, Qatar, and Kuwait. Thus, the main implication is that the GCC countries are still far away from an OCA. The success of such a union is conditional on a lot of measures including the removal of domestic and cross-border distortions that are regarded as a hamper to trade and foreign investments, the coordination of national policies that ensure macroeconomic stability, the deepening of regional integration, the development of the nonoil economy, and realization of a large degree of political integration.

Confronted with rapid economic growth and large structural changes in the economy, China's monetary authority has managed to influence the economy with its policy actions since 1983. This paper conducts a rigorous empirical test on the effect of China's monetary policy actions on its economy by properly identifying and estimating two vector autoregression (VAR) models. To identify exogenous monetary policy shocks, two identification approaches are considered in this paper: A recursive approach and the Bernanke and Mihov [Bernanke, B. S. and I. Mihov. 1998. "Measuring monetary policy." Quarterly Journal of Economics, 113(3): 869–902] procedure. We find that (i) monetary policy has unambiguous impacts on both output and prices; (ii) the relative effectiveness of policy instruments differs, i.e. money growth is an effective policy instrument but not the interest rate; (iii) changes in nominal exchange rate affect both output and prices; (iv) the liquidity effect is present. Our results favor the need to continuously reform the financial system to make it commercially driven and to have a more flexible exchange rate regime.

This study aims to explore dynamic linkages and integration among emerging markets of BRICS, especially comparing the pre- and post-BRICS formation period behaviors and further comment upon the portfolio diversification opportunities available for global investors. Weekly closing indices of BRICS stock markets for the period 2000–2020 have been taken. Considering BRICS formation year, total period is divided into two sub-periods, pre- and post-BRICS periods. Short-run relationship has been measured through Granger causality, VAR, IRF and VDC. For long-run co-movement, Johansen co-integration is applied. To explain asymmetrical response of the market, E-GARCH Model is applied. Both Granger causality and VAR model confirm presence of short-run inter-linkages among BRICS during post-BRICS period. Johansen co-integration test also establishes more co-integrating equations during post-BRICS. E-GARCH result indicates a strong presence of asymmetry effect in the volatility of BRICS stock returns during post-BRICS and concludes the presence of leverage effect in all the BRICS markets. By integrating the findings with relevant literature, authors propose a framework that establishes BRICS formation, trade agreements and collaboration with each other has resulted into a strong relationship among BRICS nations during post-BRICS period and hints a little opportunity to global investors for portfolio diversification in short-run but no opportunity in the long-run.

While the underground economy is not explicitly included in the measure of (GDP), the cocaine trade has been a major source of revenue for Colombia. Using quarterly cocaine prices from 1982 to 2007 published by the Office of National Drug Control Policy, this paper uses vector error correction and forecast error variance decomposition methods to look at the relationship between cocaine prices and the peso/$ nominal exchange rate. Our results indicate cocaine prices affect the value of the Colombian peso, which leads to some interesting policy implications.

As a developing economy, three major economic problems witnessed in the Gambia are the growing unemployment rate, migration (immigration and rural–urban drift) leading to urban population growth and the growing semi-skilled working population in the face of unemployment. This study seeks to answer the question of how the Gambian economy can plan to overcome these problems, coupled with post-COVID-19 global economic shocks, through a technically planned capacity development. In this paper, the trends in variables representing capacity development indicators, migration, unemployment and working population in the Gambia are studied using the Autoregressive Integrated Moving Average (ARIMA) model. To project a system of interrelationship among these variables in the Gambia, the study employs the Vector Autoregressive (VAR) forecast analysis for the period between 1990 and 2019, thereafter generates a five-year forecast. The findings confirm that investment into the educational sector in developing economies is bound to yield increasing return to scale in the next five years. Investment into education, training and skill acquisition, if done, will attract the transfer of technical and managerial skills and technology for the purpose of building up general national capacity in such a developing economy.

The Iranian economy is closely associated with the oil industry as a key player in the global oil market. Accordingly, oil price spikes have a major influence on government spending with oil revenues being a major source for financing different expenditure categories such as social security, education, arts and culture, and health care. Moreover, recently there have been economic sanctions imposed on Iran owing to the nuclear program which has greatly restricted Iranian oil exports and caused significant distress to government revenue which in turn has spill over effects on Iran's allocations for investment in the energy industry, and more importantly in government spending on care, education, culture and arts, and social security. This paper aims to analyse these overall effects and the impact of oil price spikes on Iranian government expenditure. In order to achieve our objective we rely on a VAR econometric model using data from 1965–2011. The results show that Iranian government social spending does not appear to be significantly affected by oil price shocks.

This article looks at the preconditions that an emerging economy needs to fulfill, before it can adopt inflation targeting as a monetary policy regime. The study is conducted using the Indian economy as a case study. We conduct sector-wise analysis of the Indian economy to evaluate the independence of India’s monetary policy from fiscal, external, structural and financial perspectives. Dominance from any of these sectors may divert monetary policy from the objective of maintaining price stability in the economy. Our analysis suggests that among the four dominance issues, the issue of “structural dominance” is the most acute for India. Supply shocks, hitting the economy due to structural bottlenecks, pose a major threat to the independent conduct of monetary policy. This study concludes that inflation band targeting with a wide target range would be a feasible monetary policy option for India.

This paper analyses the importance of ECB monetary policy shocks in the domestic activities of a non-EMU member, Croatia, with the main focus on the inflation rate. Using a Vector Autoregressive Model with an exogenous variable specification, it is found that the contraction of foreign monetary shocks have a significant positive impact on the local inflation rate and output. Interestingly, the interest rate gap exerts a statistically significant effect on the economic activities of Croatia, suggesting that targeting exchange rate stability does not eliminate the significance of ECB’s monetary policy changes.

This article connects net Japanese purchases of U.S. Treasury securities and the U.S. 10-year Treasury bond yields to the yen/dollar exchange rate. VAR estimations suggest that a one-time increase in net Japanese purchases has an immediate negative effect on U.S. long bond yields but a short-lived delayed yen depreciation. Further, a one-time increase in the U.S. long yield leads to an immediate yen depreciation. Our results support the hypothesis that Japanese investors, who are major holders of U.S. debt and face extremely low interest rates domestically, influence the dollar/yen rate in a financially integrated world.

This chapter continues the discussion of real and financial linkages in Chapter 5. From the viewpoint of world political economic development, the United States plays a very important role in the world, especially in the emerging Asia, through its IT industry. We first confirm the interdependence of the United States and the Asia-Pacific region by examining the regional trade and investment relationship between the United States and the Asia-Pacific region. We then explore the real linkage through trade and investment and the financial linkage through stock markets. These linkages are strengthened by the recent information technology (IT) revolution. The pairwise and vector autoregression (VAR) are used to test the Granger causality of real linkage in terms of GDP and the financial linkage in terms of the daily stock price indices among these countries. Impulse response functions and variance decomposition from VAR are illustrated. Our results show that there is no significant unidirectional causality from the US GDP to those of Japan, Taiwan, Korea, and China. But the slump in the US stock price indices will cause the stock market recession in Japan, Korea, and Taiwan, but not in China. Thus, the US financial condition plays an important role in these Asian countries through financial linkages.

Artificial neural network (ANN) is a prevalent tool because of its extensive adaptivity and outstanding performance. According to previous studies, Long Short-Term Memory (LSTM) neural networks generally perform well in forecasting financial time series than other models. However, few studies apply LSTM to CPI and price level forecasting. This paper separately constructs the LSTM and the Vector Autoregression (VAR) model, a classic econometric approach for time series forecasting, based on 23 factors that affect CPI directly or indirectly. The results show that the error of the LSTM is significantly lower than that of the VAR in forecasting China’s CPI, while the VAR model provides an explicit explanation of the factors of CPI forecasting through the Granger causality test. Additionally, a synthetic model combining the advantages of both generates a more satisfying outcome. This paper forecasts the CPI by combining the LSTM and VAR models for the first time and provides a new reference to the inflation forecasting area.

In this paper, we use the Vector Autoregression (VAR) approach to examine the robustness of the Phillips Curve in the United States economy from January 2020 to June 2022. The data is characterized by VAR(4) with a cointegrating rank of 2, using the unemployment rate and sticky inflation. The Impulse Response Function (IRF) is used to examine the relationship between the unemployment rate and inflation. The Granger-causal Test results suggest that historical unemployment data is useful for improving inflation projections. With a longer prediction horizon, unemployment shocks have a greater impact on the forecast error variance of inflation. Based on the impulse response function, the Phillips Curve is not alive in the US economy during the COVID-19 pandemic, but it can still be a significant factor legitimate for the government to set economic policy.

This paper examines the response of the prime rate–deposit rate spread to shocks in real output growth, inflation, and the stance of monetary policy. A simple model of the lending and deposit markets is introduced that provides insight as to how these macroeconomic factors might affect the spread. The paper employs the recently developed technique of generalized impulse response analysis proposed. This method does not impose a priori restrictions as to the relative importance each of the variables in the underlying vector autoregression may play in the transmission process. Thus, the results provide robust evidence as to the relationship between the prime rate-deposit rate spread and these macroeconomic factors. Specifically, the model suggests and the empirical results confirm that shocks to inflation widen the spread while unexpected changes in the federal funds rate and real output growth lead to a narrower spread.